Storage system performance is typically characterized by throughput metrics such as input/output operations per second (IOPS). In configuring a storage system, a customer, administrator or other user generally wants assurances that the particular configuration selected will have a very high likelihood of meeting the desired IOPS levels for its intended application environment. Unfortunately, this can be problematic under current practice. For example, the advent of software-defined storage that can run on any of a wide variety of different types of general-purpose servers or other commodity hardware has vastly increased the number of storage system configuration options that are available to users. As a result, it is generally not possible to test each and every such storage system configuration in order to ensure that it will meet IOPS requirements when deployed. It is therefore possible that a given configured storage system when actually deployed in the field may not provide the IOPS performance that was expected by its purchaser. A need therefore exists for improved techniques for estimating performance of storage systems prior to deployment but without the need for explicit testing of their particular configurations.